Modelling Safety Impacts of Automated Driving Systems in Multi-Lane Traffic

Modelling Safety Impacts of Automated Driving Systems in Multi-Lane Traffic

Mullakkal-Babu, F.A. (TU Delft Transport and Planning)

van Arem, B. (promotor)
Happee, R. (promotor)
Wang, M. (copromotor)

Delft University of Technology

2020-09-14

The past three decades have witnessed the emergence of several automotive applications that take over the task of vehicle driving on a sustained basis. The most advanced class of such applications is known as Automated Driving Systems (ADSs). ADS can autonomously operate the vehicle on road stretches that fall under its operational design domain. Industry and governments expect that such systems will be technologically feasible shortly and the traffic will be mixed with system-driven and human-driven vehicles. Even though ADSequipped vehicles will have an impact on traffic safety, there is no clarity on if they would enhance or detriment traffic safety and at what conditions and magnitude. A human and an ADS apply fundamentally different processes to acquire information, make decisions, and operate the vehicle. Therefore, our current insights on the relationship between driving behaviour and safety may not be sufficient to predict the possible impacts of ADS systems. Hence there is an urgent need to study the impacts of ADS functionalities and design factors on traffic safety.

https://doi.org/10.4233/uuid:37c8ec51-59f0-4dec-a3fa-bdd3c69e09db

TRAIL research school / School of transportation of SEU research school

978-90-5584-265-0

TRAIL Thesis Series, 2020 (6)

TRAIL Thesis Series no. T2020/6, The Netherlands Research School TRAIL

Institutional Repository

doctoral thesis

© 2020 F.A. Mullakkal-Babu